Sensitivity-Adapted Closed-Loop Optimization for High-Fidelity Controlled-Z Gates in Superconducting Qubits

TL;DR

This paper presents a sensitivity-adaptive closed-loop optimization method for designing high-fidelity, fast controlled-Z gates in superconducting qubits, achieving 99.9% fidelity in 64 ns by mitigating signal distortions.

Contribution

It introduces a novel adaptive optimization approach that enhances gate fidelity and speed in superconducting qubits through complex pulse shaping and systematic distortion mitigation.

Findings

Achieved 99.9% controlled-Z gate fidelity in 64 ns.

Compared different pulse parametrizations for optimal performance.

Implemented adaptive cost function to accelerate convergence.

Abstract

Achieving fast and high-fidelity qubit operations is crucial for unlocking the potential of quantum computers. In particular, reaching low gate errors in two-qubit gates has been a long-standing challenge in the field of superconducting qubits due to their typically long duration relative to coherence times. To realize fast gates, we utilize the hybridization between fixed-frequency superconducting qubits with a strongly interacting coupler mode that is tunable in frequency. To reduce population leakage during required adiabatic passages through avoided level crossings, we employ a sensitivity-adaptive closed-loop optimization method to design complex pulse shapes. We compare the performance of Gaussian-square, Fourier-series, and piecewise-constant-slope (PiCoS) pulse parametrizations and are able to reach 99.9 % controlled-Z gate fidelity using a 64 ns long Fourier-series pulse defined by only seven parameters. These high-fidelity values are achieved by analyzing the optimized pulse shapes to identify and systematically mitigate signal-line distortions in the experiment. To improve the convergence speed of the optimization we implement an adaptive cost function, which continuously maximizes the sensitivity. The demonstrated method can be used for tune-up and recalibration of superconducting quantum processors.